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INTRODUCTION A rough set is a formal approximation of a crisp set (i.e., conventional set) in terms of a pair of sets which give the lower and the upper approximation of the original set. The lower and upper approximation sets themselves are crisp sets in the standard version of rough set theory, but in other variations, the approximating sets may be fuzzy sets as well. A rough set is a formal approximation of a crisp set (i.e., conventional set) in terms of a pair of sets which give the lower and the upper approximation of the original set. The lower and upper approximation sets themselves are crisp sets in the standard version of rough set theory, but in other variations, the approximating sets may be fuzzy sets as well.

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MOTIVATION Customer needs identificationCustomer needs identification Why is it important?Why is it important? If needs are identified in a right manner before/during developing a product or providing a service to customers, it makes easy to design a product/service satisfying customers in a communityIf needs are identified in a right manner before/during developing a product or providing a service to customers, it makes easy to design a product/service satisfying customers in a community Needs identification is the very first step in terms of both product design and service designNeeds identification is the very first step in terms of both product design and service design Currently, few research have been developed with respect to needs identificationCurrently, few research have been developed with respect to needs identification

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CUSTOMER NEEDS IDENTIFICATION Need is a sort of internal state to do somethingNeed is a sort of internal state to do something A gap between what is and what should beA gap between what is and what should be Researchers definitionsResearchers definitions Need as a gap between actual and ideal identified as community valueNeed as a gap between actual and ideal identified as community value Wants or a demandWants or a demand Need identificationNeed identification Originated from recognizing unfulfilled needsOriginated from recognizing unfulfilled needs Consumer Buying Behavior model in managementConsumer Buying Behavior model in management Focusing on buying behavior of customersFocusing on buying behavior of customers Needs as the first step of buying procedureNeeds as the first step of buying procedure Related to customers purchase behaviorRelated to customers purchase behavior It will affect product design and service design by fulfilling unmet needsIt will affect product design and service design by fulfilling unmet needs

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CONTEXT-AWARE COMPUTING Context is a key to identify information related to customerContext is a key to identify information related to customer User context – any information characterizing the situation of an entityUser context – any information characterizing the situation of an entity Location of userLocation of user Collection of nearby people and objectsCollection of nearby people and objects Accessible devices, andAccessible devices, and Changes to objects over timeChanges to objects over time Context-aware computing technologyContext-aware computing technology It makes computer technology melt and transparently weave into our livesIt makes computer technology melt and transparently weave into our lives Context-aware computing and needs identificationContext-aware computing and needs identification Promising method to identify customer needsPromising method to identify customer needs Pattern recognition based on context related to customersPattern recognition based on context related to customers

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ROUGH SET THEORY Mathematical tool to deal with vague concepts for representing ambiguity, vagueness and general uncertaintyMathematical tool to deal with vague concepts for representing ambiguity, vagueness and general uncertainty Algebraic properties of rough sets Different algebraic semanticsAlgebraic properties of rough sets Different algebraic semantics Focus on indiscernibility and reductsFocus on indiscernibility and reducts Combination approach with Boolean reasoningCombination approach with Boolean reasoning Adopted in various researchAdopted in various research Data mining, knowledge discovery, decision support, pattern classification, and approximate reasoningData mining, knowledge discovery, decision support, pattern classification, and approximate reasoning

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REDUCTS IN INFORMATION & DECISION SYSTEM Reduct Reduct To reduce information (decision) systems by removing redundant attributes To reduce information (decision) systems by removing redundant attributes Core. A minimal set of attributes from A, the set of all attributes, that preserves the original classification defined by A. Core. A minimal set of attributes from A, the set of all attributes, that preserves the original classification defined by A.

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VALUE SET REDUCTION Discretization, used for real value attributesDiscretization, used for real value attributes

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MINIMAL DECISION RULES Construct a decision-relative discernibility function f x r by considering the row corresponding to object x in the decision-relative discernibility matrix for A. Construct a decision-relative discernibility function f x r by considering the row corresponding to object x in the decision-relative discernibility matrix for A. Compute all prime implicants of f x r. Compute all prime implicants of f x r. On the basis of the prime implicants, create minimal rules corresponding to x. To do this, consider the set A(I) of attributes corresponding to propositional variables in I, for each prime implicant I, and construct the rule: On the basis of the prime implicants, create minimal rules corresponding to x. To do this, consider the set A(I) of attributes corresponding to propositional variables in I, for each prime implicant I, and construct the rule:

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CONCLUSION Rough Set Theory (RST) is very applicable to identify needs in context-aware computing environment. Rough Set Theory (RST) is very applicable to identify needs in context-aware computing environment. RST can approximate incomplete context with approximation rules. RST can approximate incomplete context with approximation rules. RST can extract rules from context and key attributes with respect to needs by finding relationship between contexts and needs. RST can extract rules from context and key attributes with respect to needs by finding relationship between contexts and needs. RST can deal with symbolic values as well as real values. RST can deal with symbolic values as well as real values. FUTURE WORKS Implementation of context-aware needs identification system with Rough Set Theory Implementation of context-aware needs identification system with Rough Set Theory Comparing the implementation with applications using CBR and etc. Comparing the implementation with applications using CBR and etc.